Man vs machine: AI beats doctors in identifying skin cancer

Artificial intelligence (AI) is better than doctors at detecting skin cancer, according to new research.

In a study published in cancer journal Annals of Oncology, an international team of researchers trained a machine to identify skin cancer by showing it more than 100,000 images of malignant melanomas (the most deadly form of skin cancer), as well as benign moles.

The machine uses a form of artificial intelligence known as a deep learning convolutional neural network (CNN), which learns from the images it “sees” and teaches itself from what it has learned to improve its performance (a process known as machine learning).

“With each training image, the CNN improved its ability to differentiate between benign and malignant lesions,” said Professor Holger Haenssle, senior managing physician at the Department of Dermatology, University of Heidelberg, Germany.

Taking additional images that had not been used for training, the researchers then compared the machine’s performance with that of 58 dermatologists.

They found that the CNN missed fewer melanomas and misdiagnosed benign moles less often as malignant than the group of experts.

When the doctors assessed the images, they accurately detected 86.6% of malignant melanomas, and correctly identified an average of 71.3% of lesions that were not malignant. The specialists’ performance improved when they had access to close-up images and clinical information about the patient, accurately diagnosing 88.9% of malignant melanomas and 75.7% that were not cancer.

However, the AI made a correct assessment in 95% of cases based on images alone. As well as ensuring patients with cancer get the treatment they need, using the CNN in the clinical setting would potentially result in less unnecessary surgery.

The researchers said that the technology would not take over from dermatologists in diagnosing skin cancers, but could be used as an additional aid.